The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
3D Constrained Local Model for rigid and non-rigid facial tracking
Abstract
We present 3D Constrained Local Model (CLM-Z) for robust facial feature tracking under varying pose. Our approach integrates both depth and intensity information in a common framework. We show the benefit of our CLM-Z method in both accuracy and convergence rates over regular CLM formulation through experiments on publicly available datasets. Additionally, we demonstrate a way to combine a rigid head pose tracker with CLM-Z that benefits rigid head tracking. We show better performance than the current state-of-the-art approaches in head pose tracking with our extension of the generalised adaptive view-based appearance model (GAVAM).
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Cootes, T. F., Edwards, G. J., & Taylor, C. J. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.927467 · Cited by 5,409
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
Zeng, Z., Pantic, M., Roisman, G. I., & Huang, T. S. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.52 · Cited by 2,797
Machine Analysis of Facial Expressions
Pantic, M., & Stewart, M. (2007) · Face Recognition · doi:10.5772/4847 · Cited by 248
Cited by
Openface 2.0: facial behavior analysis toolkit
Baltrusaitis, T., Zadeh, A., Lim, Y. C., & Morency, L.-P. (2018) · 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018) · doi:10.1109/fg.2018.00019 · Cited by 1,861
Self-citationA review of affective computing: From unimodal analysis to multimodal fusion
Poria, S., Cambria, E., Bajpai, R., & Hussain, A. (2017) · Information Fusion · doi:10.1016/j.inffus.2017.02.003 · Cited by 1,644
(2014) · doi:10.5555/2615731.2617415 · Cited by 553
Poria, S., Cambria, E., & Gelbukh, A. (2015) · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d15-1303 · Cited by 533
Constrained Local Neural Fields for Robust Facial Landmark Detection in the Wild
Baltrusaitis, T., Robinson, P., & Morency, L.-P. (2013) · 2013 IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2013.54 · Cited by 415
Self-citation
Metadata
- Authors
- Baltrusaitis, T., Robinson, P., & Morency, L.
- Venue
- 2012 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2012-06
- Pages
- 2610-2617
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2151802865
- Cited by
- 313
- References
- 3
- FWCI
- 19.60
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: 3D Constrained Local Model for rigid and non-rigid facial tracking. https://app.cochat.ai/papers/10.1109/cvpr.2012.6247980
- The paper
- Baltrusaitis, T., Robinson, P., & Morency, L. (2012). 3D Constrained Local Model for rigid and non-rigid facial tracking. 2012 IEEE Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.2012.6247980
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.